Senior Data Scientist (Maternity Cover) - (Logistics, Workforce)

As the world’s pioneering local delivery platform, our mission is to deliver an amazing experience, fast, easy, and to your door. We operate in around 65 countries worldwide, powered by tech, designed by people. As one of Europe’s largest tech platforms, headquartered in Berlin, Germany, Delivery Hero has been listed on the Frankfurt Stock Exchange since 2017 and is part of the MDAX stock market index. We push hard, learn quickly and stay human along the way. It’s this wonderful mix of high performance and real community that makes Delivery Hero a place where ambition and belonging grow side by side. If you’re curious, collaborative and ready to dive deep into meaningful work, you’ll fit right in.

We are looking for a Senior Data Scientist (Maternity Cover) to join our Logistics team to help us create a fast, reliable and transparent delivery experience. You will make an impact in optimizing our on-demand last-mile delivery operations, involving hundreds of thousands of couriers and restaurants, improving the experience for millions orders per day in 65+ countries.

In our Logistics Team, you’ll tackle high-impact challenges that make last-mile delivery efficient, affordable, and sustainable. Your work will directly improve experiences for riders, end customers, and merchants across the globe. Each enhancement you contribute will help Delivery Hero optimize delivery operations, supporting expansion into new areas like grocery and retail.

Your mission

- Conceptualize the right modeling approach for challenges in the field of Logistics at scale, together with your squad lead and our stakeholders.
- Innovate new modeling solutions by drawing from fields like Machine Learning, Operations Research and Statistics that drive value for our business.
- Pair-program with your squad to engineer solutions that automate the retraining of models and generation of predictions.
- Provide ideas in brainstorming sessions with your Data Science colleagues to solve the toughest modeling problems together.
- Help defining data needs to bring value to the projects, collaborate with the data engineering and tech teams in planning their roadmap.
- Work with (semi-)structured data from our BigQuery DWH architecture and process with Spark where necessary.

Requirements

You have at least 5 years of experience applying methods from machine learning to real-world datasets.; Fluency in Python and familiarity with its scientific/visualization libraries such as NumPy numpy, Ppandas, Sscikit-learn, Mmatplotlib, Pplotly etc.; You can transfer business problems from a problem space to a technical solution space.; Experience in solving regression and classification-typeclassification type of problems with statistical, linear/non-linear models and ensemble models in particular (Random Forest/XGBoost/LightGBM/CatBoost).; Experience with Time-Series Forecasting, Operations Research, and Statistics is an interesting addition; You know how to work with Big Data platforms such as Big Query/Spark and know how to write a SQL query to pull the data you need.; You can write maintainable code that follows best practices in software engineering.